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Innovative Approaches to Task Scheduling in cloud computing Environments Using an Advanced Willow Catkin Optimization Algorithm

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Computers, Materials & Continua 2025年第2期82卷 2495-2520页

作者： Jeng-Shyang Pan Na Yu Shu-Chuan Chu An-Ning Zhang Bin Yan Junzo Watada College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China Department of Information Management Chaoyang University of TechnologyTaichung41349Taiwan College of Electronics Communication and PhysicsShandong University of Science and TechnologyQingdao266590China Graduate School of Information Production and SystemsWaseda UniversityKitakyushu808-0135Japan

The widespread adoption of cloud computing has underscored the critical importance of efficient resource allocation and management, particularly in task scheduling, which involves assigning tasks to computing resources for optimized resource utilization. Several meta-heuristic algorithms have shown effectiveness in task scheduling, among which the relatively recent Willow Catkin Optimization (WCO) algorithm has demonstrated potential, albeit with apparent needs for enhanced global search capability and convergence speed. To address these limitations of WCO in cloud computing task scheduling, this paper introduces an improved version termed the Advanced Willow Catkin Optimization (AWCO) algorithm. AWCO enhances the algorithm’s performance by augmenting its global search capability through a quasi-opposition-based learning strategy and accelerating its convergence speed via sinusoidal mapping. A comprehensive evaluation utilizing the CEC2014 benchmark suite, comprising 30 test functions, demonstrates that AWCO achieves superior optimization outcomes, surpassing conventional WCO and a range of established meta-heuristics. The proposed algorithm also considers trade-offs among the cost, makespan, and load balancing objectives. Experimental results of AWCO are compared with those obtained using the other meta-heuristics, illustrating that the proposed algorithm provides superior performance in task scheduling. The method offers a robust foundation for enhancing the utilization of cloud computing resources in the domain of task scheduling within a cloud computing environment.

关键词： Willow catkin optimization algorithm cloud computing task scheduling opposition-based learning strategy

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cloud computing-enabled IIOT system for neurosurgical simulation using augmented reality data acces

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Digital Communications and Networks 2023年第2期9卷 347-357页

作者： Jun Liu Kai Qian Zhibao Qin Mohammad Dahman Alshehri Qiong Li Yonghang Tai Yunnan Key Laboratory of Opto-electronic Information Technology Yunnan Normal UniversityKunming650500China Department of Thoracic Surgery Institute of The First People's Hospital of Yunnan ProvinceKunmingChina Faculty of Life and Biotechnology Kunming University of Science and TechnologyKunmingChina Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

In recent years,statistics have indicated that the number of patients with malignant brain tumors has increased ***,most surgeons still perform surgical training using the traditional autopsy and prosthesis model,which encounters many problems,such as insufficient corpse resources,low efficiency,and high *** the advent of the 5G era,a wide range of Industrial Internet of Things(IIOT)applications have been *** Reality(VR)and Augmented Reality(AR)technologies that emerged with 5G are developing rapidly for intelligent medical *** address the challenges encountered during neurosurgery training,and combining with cloud computing,in this paper,a highly immersive AR-based brain tumor neurosurgery remote collaborative virtual surgery training system is developed,in which a VR simulator is *** system enables real-time remote surgery training interaction through 5G *** experts and 18 novices were invited to participate in the experiment to verify the ***,the two simulators were evaluated using face and construction validation *** results obtained by training the novices 50 times were further analyzed using the Learning Curve-Cumulative Sum(LC-CUSUM)evaluation method to validate the effectiveness of the two *** results of the face and content validation demonstrated that the AR simulator in the system was superior to the VR simulator in terms of vision and scene authenticity,and had a better effect on the improvement of surgical ***,the surgical training scheme proposed in this paper is effective,and the remote collaborative training effect of the system is ideal.

关键词： Neurosurgery IIOT cloud computing Intelligent medical 5G AR

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cloud computing-Based Forensic Analysis for Collaborative Network Security Management System

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Tsinghua Science and Technology 2013年第1期18卷 40-50页

作者： Zhen Chen Fuye Han Junwei Cao Xin Jiang Shuo Chen Research Institute of Information Technology and Tsinghua National Laboratory for Information Science and Technology (TNList) Tsinghua University Department of Computer Science and Technology Research Institute of Information Technology and Tsinghua National Laboratory for Information Science and Technology (TNList) Tsinghua University Department of Automation Research Institute of Information Technology and Tsinghua National Laboratory for Information Science and Technology (TNList)Tsinghua University

Internet security problems remain a major challenge with many security concerns such as Internet worms, spam, and phishing attacks. Botnets, well-organized distributed network attacks, consist of a large number of bots that generate huge volumes of spam or launch Distributed Denial of Service （DDoS） attacks on victim hosts. New emerging botnet attacks degrade the status of Internet security further. To address these problems, a practical collaborative network security management system is proposed with an effective collaborative Unified Threat Management （UTM） and traffic probers. A distributed security overlay network with a centralized security center leverages a peer-to-peer communication protocol used in the UTMs collaborative module and connects them virtually to exchange network events and security rules. Security functions for the UTM are retrofitted to share security rules. In this paper, we propose a design and implementation of a cloud-based security center for network security forensic analysis. We propose using cloud storage to keep collected traffic data and then processing it with cloud computing platforms to find the malicious attacks. As a practical example, phishing attack forensic analysis is presented and the required computing and storage resources are evaluated based on real trace data. The cloud- based security center can instruct each collaborative UTM and prober to collect events and raw traffic, send them back for deep analysis, and generate new security rules. These new security rules are enforced by collaborative UTM and the feedback events of such rules are returned to the security center. By this type of close-loop control, the collaborative network security management system can identify and address new distributed attacks more quickly and effectively.

关键词： cloud computing overlay network collaborative network security system computer forensics anti-botnet anti-phishing hadoop file system eucalyptus amazon web service

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An Anomalous Behavior Detection Model in cloud computing

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Tsinghua Science and Technology 2016年第3期21卷 322-332页

作者： Xiaoming Ye Xingshu Chen Haizhou Wang Xuemei Zeng Guolin Shao Xueyuan Yin Chun Xu College of Computer Science Cybersecurity Research Institute Sichuan University

This paper proposes an anomalous behavior detection model based on cloud computing. Virtual Machines （VMs） are one of the key components of cloud Infrastructure as a Service （laaS）. The security of such VMs is critical to laaS security. Many studies have been done on cloud computing security issues, but research into VM security issues, especially regarding VM network traffic anomalous behavior detection, remains inadequate. More and more studies show that communication among internal nodes exhibits complex patterns. Communication among VMs in cloud computing is invisible. Researchers find such issues challenging, and few solutions have been proposed--leaving cloud computing vulnerable to network attacks. This paper proposes a model that uses Software-Defined Networks （SDN） to implement traffic redirection. Our model can capture inter-VM traffic, detect known and unknown anomalous network behaviors, adopt hybrid techniques to analyze VM network behaviors, and control network systems. The experimental results indicate that the effectiveness of our approach is greater than 90%, and prove the feasibility of the model.

关键词： virtual machine network behavior anomaly detection cloud computing

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Experience Availability： Tail-Latency Oriented Availability in Software-Defined cloud computing

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Journal of Computer Science & Technology 2017年第2期32卷 250-257页

作者： Bin-Lei Cai Rong-Qi Zhang Xiao-Bo Zhou Lai-Ping Zhao Ke-Qiu Li Tianjin Key Laboratory of Advanced Networking School of Computer Science and Technology Tianjin University Tianjin 300350 China School of Computer Software Tianjin University Tianjin 300350 China

Resource sharing, multi-tenant interference and bursty workloads in cloud computing lead to high tail-latency that severely affects user quality of experience （QoE）, where response latency is a critical factor. A lot of research efforts are dedicated to reducing high tail-latency and improving user QoE, such as software-defined cloud computing （SDC）. However, the traditional availability analysis of cloud computing captures the pure failure-repair behavior with user QoE ignored. In this paper, we propose a conceptual framework, experience availability, to properly assess the effectiveness of SDC while taking into account both availability and response latency simultaneously. We review the related work on availability models and methods of cloud systems, and discuss open problems for evaluating experience availability in SDC. We also show some of our preliminary results to demonstrate the feasibility of our ideas.

关键词： cloud computing software-defined cloud computing (SDC) availability tail-latency

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EABDS: Attribute-Based Secure Data Sharing with Efficient Revocation in cloud computing

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Chinese Journal of Electronics 2015年第4期24卷 862-868页

作者： HUANG Qinlong MA Zhaofeng YANG Yixian FU Jingyi NIU Xinxin Information Security Center Beijing University of Posts and Telecommunications National Engineering Laboratory for Disaster Backup and Recovery Beijing University of Posts and Telecommunications

Ciphertext-policy attribute-based encryption(CP-ABE) is becoming a promising solution to guarantee data security in cloud computing. In this paper,we present an attribute-based secure data sharing scheme with Efficient revocation(EABDS) in cloud *** scheme first encrypts data with Data encryption key(DEK) using symmetric encryption and then encrypts DEK based on CP-ABE, which guarantees the data confidentiality and achieves fine-grained access control. In order to solve the key escrow problem in current attribute based data sharing schemes, our scheme adopts additively homomorphic encryption to generate attribute secret keys of users by attribute authority in cooperation with key server, which prevents attribute authority from accessing the data by generating attribute secret keys *** scheme presents an immediate attribute revocation method that achieves both forward and backward *** computation overhead of user is also reduced by delegating most of the decryption operations to the key *** security and performance analysis results show that our scheme is more secure and efficient.

关键词： Attribute-based encryption Data sharing Attribute revocation Key escrow cloud computing

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Toward cloud computing QoS Architecture:Analysis of cloud Systems and cloud Services

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IEEE/CAA Journal of Automatica Sinica 2017年第1期4卷 6-18页

作者： Mohammad Hossein Ghahramani MengChu Zhou Chi Tin Hon IEEE Institute of Systems Engineering Macao University of Science and Technology Helen and John C. Hartmann Department of Electrical and Computer Engineering New Jersey Institute of Technology School of Management Fudan University

cloud can be defined as a new computing paradigm that provides scalable, on-demand, and virtualized resources for users. In this style of computing, users can access a shared pool of computing resources which are provisioned with minimal management efforts of users. Yet there are some obstacles and concerns about the use of clouds. Guaranteeing quality of service QoS by service providers can be regarded as one of the main concerns for companies tending to use it. Service provisioning in clouds is based on service level agreements representing a contract negotiated between users and providers. According to this contract, if a provider cannot satisfy its agreed application requirements, it should pay penalties as compensation. In this paper, we intend to carry out a comprehensive survey on the models proposed in literature with respect to the implementation principles to address the QoS guarantee issue. © 2014 Chinese Association of Automation.

关键词： cloud computing Distributed computer systems System of systems Systems engineering Telecommunication services Web services

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An online service-oriented performance profiling tool for cloud computing systems

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Frontiers of Computer Science 2013年第3期7卷 431-445页

作者： Haibo MI Huaimin WANG Yangfan ZHOU Michael Rung-Tsong LY~ Hua CAI Gang YIN National Lab for Parallel & Distributed Processing National University of Defense Technology Changsha 410073 China Shenzhen Research Institute The Chinese University of Hong Kong Shenzhen 518000 China computing Platform Alibaba Cloud Computing Company Hangzhou 310000 China

The growing scale and complexity of component interactions in cloud computing systems post great challenges for operators to understand the characteristics of system performance. Profiling has long been proved to be an effective approach to performance analysis; however, existing approaches confront new challenges that emerge in cloud computing systems. First, the efficiency of the profiling becomes of critical concern; second, service-oriented profiling should be considered to support separation-of-concerns performance analysis. To address the above issues, in this paper, we present P-Tracer, an online performance profiling tool specifically tailored for cloud computing systems. P-Tracer constructs a specific search engine that proactively processes performance logs and generates a particular index for fast queries; second, for each service, P-Tracer retrieves a statistical insight of performance characteristics from multi-dimensions and provides operators with a suite of web-based interfaces to query the critical information. We evaluate P- Tracer in the aspects of tracing overheads, data preprocessing scalability and querying efficiency. Three real-world case studies that happened in Alibaba cloud computing platform demonstrate that P-Tracer can help operators understand soft-ware behaviors and localize the primary causes of performance anomalies effectively and efficiently.

关键词： cloud computing performance profiling performance anomaly visual analytics

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A benefit-aware on-demand provisioning approach for multi-tier applications in cloud computing

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Frontiers of Computer Science 2013年第4期7卷 459-474页

作者： Heng WU Wenbo ZHANG Jianhua ZHANG Jun WEI Tao HUANG Institute of Software Chinese Academy of Sciences Beijing 100190 China State Key Laboratory Computer Science Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China

Dynamic resource provisioning is a challenging technique to meet the service level agreement （SLA） requirements of multi-tier applications in virtualization-based cloud computing. Prior efforts have addressed this challenge based on either a cost-oblivious approach or a cost-aware approach. However, both approaches may suffer frequent SLA violations under flash crowd conditions. Because they ignore the benefit gained that a multi-tier application continuously guarantees the SLA in the new configuration. In this paper, we propose a benefit-aware approach with feedback control theory to solve this problem. Experimental results based on live workload traces show that our approach can reduce resource provisioning cost by as much as 30% compared with a costoblivious approach, and can effectively reduce SLA viola- tions compared with a cost-aware approach.

关键词： cloud computing visualization resource recon-figuration feedback control benefit-aware

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Low-cost cloud computing solution for geo-information processing

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Journal of Central South University 2016年第12期23卷 3217-3224页

作者：高培超刘钊谢美慧田琨 Department of Land Surveying and Geo-Informatics Hong Kong Polytechnic University Institute of Geomatics Department of Civil EngineeringTsinghua University

cloud computing has emerged as a leading computing paradigm,with an increasing number of geographic information(geo-information) processing tasks now running on *** this reason,geographic information system/remote sensing(GIS/RS) researchers rent more public clouds or establish more private ***,a large proportion of these clouds are found to be underutilized,since users do not deal with big data every *** low usage of cloud resources violates the original intention of cloud computing,which is to save resources by improving *** this work,a low-cost cloud computing solution was proposed for geo-information processing,especially for temporary processing *** proposed solution adopted a hosted architecture and can be realized based on ordinary computers in a common GIS/RS *** usefulness and effectiveness of the proposed solution was demonstrated by using big data simplification as a case *** to commercial public clouds and dedicated private clouds,the proposed solution is more low-cost and resource-saving,and is more suitable for GIS/RS applications.

关键词： cloud computing geo-information processing geo-processing

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